Spatial patterns of tipping points in global vegetation data

Climate change may lead to tipping points where ecosystems shift to alternative states (i.e. grassland to desert). New theory suggests that tipping points may not be uniform but display distinctive spatial patterns.

In this project, we will test if such patterns occur for vegetation globally, using new spatio-temporal global datasets.

This work has potentially major implications for understanding how natural terrestrial systems will respond to climate change in the coming decades.